nzilbb.vowels (version 0.4.3)

pca_rotate_procrustes: Apply Procrustes rotation to PCA loadings and scores.

Description

It is sometimes convenient to rotate principal components to align PCA applied to one dataset with PCA applied to another. This function allows for Procrustes rotation of Principal Components, without scaling. That is, we rotate and/or flip loadings or scores so that the PCA analyses to be rotated most closely matches the loadings (or scores) from the target PCA analysis.

Usage

pca_rotate_procrustes(
  to_rotate,
  target,
  max_pcs,
  rotate = "loadings",
  rotation_variables = "all"
)

Value

an object matching the class of to_rotate.

Arguments

to_rotate

an object of class princomp or prcomp.

target

an object of class princomp or prcomp

max_pcs

an integer. Rotation will be applied from PC1 up to max_pcs.

rotate

a string, either "loadings" or "scores", to identify whether the loadings of to_rotate should be aligned with target or the scores (default: "loadings")

rotation_variables

a string, names of variables to be used in the rotation. Applied to rotation of loadings when two datasets have only partial overlap of variables. (default: "all", which uses all variables).

Details

NB: rotated components are not principal components. They no longer explain maximal variance. Rotated components should not be referred to as 'principal components'. The simplest approach is just to call them 'components' after describing the rotation. This function modifies objects of the class 'prcomp' and 'princomp', adding an additional 'note' which collects all the rotations which have been applied. This allows any plotting function which works with the outputs of prcomp() or princomp() to work. This may result in plots which incorrectly identify rotated components as principal components. Be careful not to include any such plot in a research output.

Examples

  # PCA on a subset of ONZE speakers
  onze_pca <- prcomp(
    onze_intercepts |> dplyr::select(-speaker),
    scale = TRUE
   )

   # PCA on all ONZE speakers
   onze_full <- prcomp(
    onze_intercepts_full |> dplyr::select(-speaker),
    scale = TRUE
   )

   # rotate subset to match loadings of `onze_full`
   rotated_pca <- onze_pca |>
     pca_rotate_procrustes(
       onze_full, max_pcs = 5
     )